Clustering Challenges in Biological Networks PDF Download
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Author: Sergiy Butenko
Publisher: World Scientific
ISBN: 9812771662
Category : Science
Languages : en
Pages : 347
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Book Description
This text offers introductory knowledge of a wide range of clustering and other quantitative techniques used to solve biological problems.
Author: Sergiy Butenko
Publisher: World Scientific
ISBN: 9812771662
Category : Science
Languages : en
Pages : 347
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Book Description
This text offers introductory knowledge of a wide range of clustering and other quantitative techniques used to solve biological problems.
Author: Sergiy Butenko
Publisher: World Scientific
ISBN: 9812771654
Category : Science
Languages : en
Pages : 347
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Book Description
This text offers introductory knowledge of a wide range of clustering and other quantitative techniques used to solve biological problems.
Author: Patrick Doreian
Publisher: John Wiley & Sons
ISBN: 1119224705
Category : Mathematics
Languages : en
Pages : 425
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Book Description
Provides an overview of the developments and advances in the field of network clustering and blockmodeling over the last 10 years This book offers an integrated treatment of network clustering and blockmodeling, covering all of the newest approaches and methods that have been developed over the last decade. Presented in a comprehensive manner, it offers the foundations for understanding network structures and processes, and features a wide variety of new techniques addressing issues that occur during the partitioning of networks across multiple disciplines such as community detection, blockmodeling of valued networks, role assignment, and stochastic blockmodeling. Written by a team of international experts in the field, Advances in Network Clustering and Blockmodeling offers a plethora of diverse perspectives covering topics such as: bibliometric analyses of the network clustering literature; clustering approaches to networks; label propagation for clustering; and treating missing network data before partitioning. It also examines the partitioning of signed networks, multimode networks, and linked networks. A chapter on structured networks and coarsegrained descriptions is presented, along with another on scientific coauthorship networks. The book finishes with a section covering conclusions and directions for future work. In addition, the editors provide numerous tables, figures, case studies, examples, datasets, and more. Offers a clear and insightful look at the state of the art in network clustering and blockmodeling Provides an excellent mix of mathematical rigor and practical application in a comprehensive manner Presents a suite of new methods, procedures, algorithms for partitioning networks, as well as new techniques for visualizing matrix arrays Features numerous examples throughout, enabling readers to gain a better understanding of research methods and to conduct their own research effectively Written by leading contributors in the field of spatial networks analysis Advances in Network Clustering and Blockmodeling is an ideal book for graduate and undergraduate students taking courses on network analysis or working with networks using real data. It will also benefit researchers and practitioners interested in network analysis.
Author: Björn H. Junker
Publisher: John Wiley & Sons
ISBN: 1118209915
Category : Computers
Languages : en
Pages : 278
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Book Description
An introduction to biological networks and methods for their analysis Analysis of Biological Networks is the first book of its kind to provide readers with a comprehensive introduction to the structural analysis of biological networks at the interface of biology and computer science. The book begins with a brief overview of biological networks and graph theory/graph algorithms and goes on to explore: global network properties, network centralities, network motifs, network clustering, Petri nets, signal transduction and gene regulation networks, protein interaction networks, metabolic networks, phylogenetic networks, ecological networks, and correlation networks. Analysis of Biological Networks is a self-contained introduction to this important research topic, assumes no expert knowledge in computer science or biology, and is accessible to professionals and students alike. Each chapter concludes with a summary of main points and with exercises for readers to test their understanding of the material presented. Additionally, an FTP site with links to author-provided data for the book is available for deeper study. This book is suitable as a resource for researchers in computer science, biology, bioinformatics, advanced biochemistry, and the life sciences, and also serves as an ideal reference text for graduate-level courses in bioinformatics and biological research.
Author: Mark Buchanan
Publisher: Cambridge University Press
ISBN: 0521882737
Category : Science
Languages : en
Pages : 282
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Book Description
Key introductory text for graduate students and researchers in physics, biology and biochemistry.
Author: Sourav S. Bhowmick
Publisher: Springer
ISBN: 331954621X
Category : Computers
Languages : en
Pages : 159
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Book Description
This book focuses on the data mining, systems biology, and bioinformatics computational methods that can be used to summarize biological networks. Specifically, it discusses an array of techniques related to biological network clustering, network summarization, and differential network analysis which enable readers to uncover the functional and topological organization hidden in a large biological network. The authors also examine crucial open research problems in this arena. Academics, researchers, and advanced-level students will find this book to be a comprehensive and exceptional resource for understanding computational techniques and their applications for a summary of biological networks.
Author: Charu C. Aggarwal
Publisher: CRC Press
ISBN: 1466558229
Category : Business & Economics
Languages : en
Pages : 648
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Book Description
Research on the problem of clustering tends to be fragmented across the pattern recognition, database, data mining, and machine learning communities. Addressing this problem in a unified way, Data Clustering: Algorithms and Applications provides complete coverage of the entire area of clustering, from basic methods to more refined and complex data clustering approaches. It pays special attention to recent issues in graphs, social networks, and other domains. The book focuses on three primary aspects of data clustering: Methods, describing key techniques commonly used for clustering, such as feature selection, agglomerative clustering, partitional clustering, density-based clustering, probabilistic clustering, grid-based clustering, spectral clustering, and nonnegative matrix factorization Domains, covering methods used for different domains of data, such as categorical data, text data, multimedia data, graph data, biological data, stream data, uncertain data, time series clustering, high-dimensional clustering, and big data Variations and Insights, discussing important variations of the clustering process, such as semisupervised clustering, interactive clustering, multiview clustering, cluster ensembles, and cluster validation In this book, top researchers from around the world explore the characteristics of clustering problems in a variety of application areas. They also explain how to glean detailed insight from the clustering process—including how to verify the quality of the underlying clusters—through supervision, human intervention, or the automated generation of alternative clusters.
Author: Sungchul Ji
Publisher: Springer Science & Business Media
ISBN: 1461421519
Category : Science
Languages : en
Pages : 751
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Book Description
The book presents the first comprehensive molecular theory of the living cell ever published since the cell doctrine was formulated in 1838-1839. It introduces into cell biology over thirty key concepts, principles and laws imported from physics, chemistry, computer science, linguistics, semiotics and philosophy. The author formulates physically, chemically and enzymologically realistic molecular mechanisms to account for basic living processes such as ligand-receptor interactions, enzymic catalysis, force-generating mechanisms in molecular motors, chromatin remodelling, and signal transduction. Possible solutions to basic and practical problems facing contemporary biology and biomedical sciences have been suggested, including pharmacotherapeutics and personalized medicine.
Author: Ying Tan
Publisher: Springer
ISBN: 3319409735
Category : Computers
Languages : en
Pages : 564
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Book Description
The LNCS volume LNCS 9714 constitutes the refereed proceedings of the International Conference on Data Mining and Big Data, DMBD 2016, held in Bali, Indonesia, in June 2016. The 57 papers presented in this volume were carefully reviewed and selected from 115 submissions. The theme of DMBD 2016 is "Serving Life with Data Science". Data mining refers to the activity of going through big data sets to look for relevant or pertinent information.The papers are organized in 10 cohesive sections covering all major topics of the research and development of data mining and big data and one Workshop on Computational Aspects of Pattern Recognition and Computer Vision.
Author: Yang Xiang
Publisher: Springer
ISBN: 3642246699
Category : Computers
Languages : en
Pages : 431
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Book Description
This two volume set LNCS 7016 and LNCS 7017 constitutes the refereed proceedings of the 11th International Conference on Algorithms and Architectures for Parallel Processing, ICA3PP 2011, held in Melbourne, Australia, in October 2011. The second volume includes 37 papers from one symposium and three workshops held together with ICA3PP 2011 main conference. These are 16 papers from the 2011 International Symposium on Advances of Distributed Computing and Networking (ADCN 2011), 10 papers of the 4th IEEE International Workshop on Internet and Distributed Computing Systems (IDCS 2011), 7 papers belonging to the III International Workshop on Multicore and Multithreaded Architectures and Algorithms (M2A2 2011), as well as 4 papers of the 1st IEEE International Workshop on Parallel Architectures for Bioinformatics Systems (HardBio 2011).
